Analysis of spatial fixed PV arrays configurations to maximize energy harvesting in BIPV applications

NOTICE: this is the author’s version of a work that was accepted for publication in RENEWABLE ENERGY. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in RENEWABLE ENERGY, [VOL.75, MARCH 2015] DOI 10.1016/j.renene.2014.10.041 Analysis of spatial fixed PV arrays configurations to maximize energy harvesting in BIPV applications Berk Celika, Engin Karatepea,*, Santiago Silvestreb, Nuri Gokmena, Aissa Chouderc aDepartment of Electrical and Electronics Engineering, Ege University, 35100 Bornova, Izmir, Turkey bMNT Group, Electronic Engineering Department, Universitat Politècnica de Catalunya BarcelonaTECH, C/Jordi Girona 1-3, Campus Nord UPC, 08034 Barcelona, Spain cElectrical Engineering Department, Faculty of Technology, University of M'sila BP 166 Ichbilia, Algeria Abstract − This paper presents a new approach for efficient utilization of building integrated photovoltaic (BIPV) systems under partial shading conditions in urban areas. The aim of this study is to find out the best electrical configuration by analyzing annual energy generation of the same BIPV system, in terms of nominal power, without changing physical locations of the PV modules in the PV arrays. For this purpose, the spatial structure of the PV system including the PV modules and the surrounding obstacles is taken into account on the basis of virtual reality environment. In this study, chimneys which are located on the residential roof-top area are considered to create the effect of shading over the PV array. The locations of PV modules are kept stationary, which is the main point of this paper, while comparing the performances of the configurations with the same surrounding obstacles that causes partial shading conditions. The same spatial structure with twelve distinct PV array configurations is considered. The same settling conditions on the roof-top area allow fair comparisons between PV array configurations. 1 The payback time analysis is also performed with considering local and global maximum power points (MPPs) of PV arrays by comparing the annual energy yield of the different configurations. Keywords: BIPV systems; PV configurations; Partial shading; Virtual reality; Payback time *Corresponding Author. Tel.: +90 232 3115243; Fax: +90 232 3886024 E-mail address: engin.[email protected]; [email protected]m (E. Karatepe). 1. Introduction Physical placement of the photovoltaic (PV) modules on the planned installation surface is one of the major steps for efficient utilization of PV systems in building integrated photovoltaic (BIPV) applications. One of the most important advantages of PV modules is their modular structure, hence they can be simply adopted in existing buildings and can be installed anywhere [1]. However, PV system performance is affected by several environmental and physical factors such as shading effects of the environmental obstacles, specifications of the PV array area, tilt and azimuth angles of the mounting surface [2-4]. The partial shading effect is one of the most important issues in terms of power reduction in BIPV systems. It is difficult to avoid partial shading effects along the year due to the neighboring obstacles around BIPV systems. Under partial shading conditions, the PV arrays present highly nonlinear power-voltage (P-V) curves depending on the irradiance values and the number of shaded PV modules. In this situation, the conventional maximum power point tracking (MPPT) methods cannot track the global maximum power point on the P-V curve. Therefore, there are a number of studies on development of advanced global MPPTs methods to reduce the power losses due to partial shading effects [5-9]. On the other hand, another approach for reducing partial shading effect is to find out available installation areas where the PV modules are minimally affected by partial shading effect. In the 2 literature, different techniques have been presented in order to estimate available area for the installation of PV modules [10, 11]. In these studies, software packages are used to find the nonshaded areas or minimum shaded areas during the day. Loulas et al. studied on the estimation of the potential PV systems on buildings by using Google Sketchup and PVsyst for detailed shading analysis in Greece [10]. Strzalka et al. worked on the 3D modeling of large city areas to estimate the PV energy generation by using Geographic Information System (GIS) in Germany [10]. These studies focused on the estimation of the suitable area to avoid the shading effect in PV array due to the surrounding obstacles. However, it is not always feasible in BIPV systems because of the lack of spaces for installing the PV modules to a different place. Another approach to reduce the mismatch losses due to the shading effect is the using of different PV array configurations [12-14]. Rani et al. reconfigured the physical location of the PV modules in the PV array according to a Su Do Ku puzzle pattern to improve the performance of the system under partially shaded conditions without altering the electrical connection [14]. On the other hand, it is possible to change the global MPP on the P-V curve by different PV array configurations without changing the physical location of PV modules. In conventional series-parallel (SP) configuration, the MPPs usually move to the short circuit point on the P-V curve under partial shading conditions. Therefore, if the global MPP of P-V curve can be kept near the open circuit voltage by only changing the configuration type, the harvested energy from PV array can be increased by using a simple conventional MPPT method in a narrow voltage window [13]. Generally, PV modules are connected to each other by SP configuration. However, a new configuration called as the total cross tied (TCT) can be more advantageous than the SP configuration [12, 13]. This study evaluates different electrical configuration types without changing the physical location of PV modules considering realistic partial shading conditions in BIPV systems. In this 3 study, PV array is built up by 24 PV modules and electrical configurations of the PV array are designed as 2x12, 3x8, 4x6, 12x2, 8x3, and 6x4 for TCT and SP types. The locations of PV modules are kept stationary, which is the main point of this paper, while comparing the performances of the configurations with the same surrounding obstacles that causes partial shading conditions. The payback time analysis is also performed by comparing annual harvesting energies in different configurations of the PV arrays. 2. Methodology The proposed methodology has three main phases. The first phase deals with the spatial behavior of the shadow on the PV array. This phase includes the identification of the shadow of surrounding obstacles, detection of the shadow on the PV module surfaces, and solar irradiance calculations. The partial shading analysis of fixed located PV array configurations presented in this work is based on the previous study [15] that presents the structure of trigonometric equations and procedures of the shadowing model for a PV array. When evaluating the performance of PV systems, solar irradiance data is required to determine the potential energy yield over the year. In this study, the solar irradiance values are taken from ASHRAE formulations [16]. In the second phase, the electrical behavior of PV array is analyzed. The second phase consists of two stages: constructing equivalent circuit based model of PV arrays and assigning of solar irradiance values to the PV modules according to the shadow conditions. In this study, the model of BP 3125J PV module is used on virtual reality simulations. The PV module parameters are given in Table 1. The module consists of 36 solar cells, and 18 cells are equipped with one bypass diode. Since each PV module has two bypass diodes, one PV module shows two PV module characteristics. The single PV module can be divided into two parts to reduce the 4 computational efforts and each part behaves as a single module [17]. It allows that two one-diode equivalent circuit models are enough to represent the behavior of a single PV module characteristic. The model of a PV module is given in Fig. 1. Each bypass diode part of a PV module is named by the left side and right side as shown in Fig. 1. Table 1 Typical electric characteristic of BP 3125J Parameters Standard Test Condition Maximum power 125 W Voltage at Pmax (Vmax) 17.40 V Current at P max (I max ) 7.20 A Short circuit current 8.10 A Open circuit voltage 22.0 Module efficiency (%) 12.3 Diodes 2 Bypass diodes Module dimensions 1510x674x50 mm For a realistic simulation in PV systems, the physical dimension of PV module is a very important parameter as well as electrical parameters for observation of the partial shading effects on the harvested energy. In simulation studies, PV cell based model can be used for detailed PV analysis. However, it causes to increase computational time significantly because a PV module consists of multiple individual solar cells connected in series. In a typical module, solar cells are connected in series to increase the power and voltage. Moreover, in a PV array, individual PV modules are connected in both series and parallel. For this reason, bypass diode based model can be used to reduce the computational efforts [17, 18]. Karatepe et al. [17] present an analysis method to reflect the mismatch effects as well as solar cell based analysis without increasing 5 computational time, in a simple manner and with sufficient degree of precision. In this study, PV array consists of 24 PV modules and each module has two bypass diodes to avoid from hot spot effect of partial shading. In the third phase, the harvested energy is calculated at local and global MPPs in order to determine payback time of different PV array configurations. In this phase, the performance analyses of the different electrical configurations are compared by payback time under the same partial shading conditions. In addition, the MPP is also observed under uniform irradiance condition for comparison purposes by removing the surrounding obstacles that cause partial shading conditions. Fig. 1. PV module model (a) physical structure (b) electrical structure. 3. Shadowing Model The PV modules can be shaded due to the different reasons through the year. However, all reasons are not schedulable by using deterministic methods, such as cloud passing, dust or bird dropping. On the other hand, the effect of surrounding obstacles around the PV array can be observed and analyzed by suitable virtual reality simulations. In this study, two chimneys are considered for partial shading observations on the PV array which are placed on the rooftop of a building. The installations of PV modules and two chimneys are represented in Fig. 2. 6 Fig. 2. BIPV rooftop PV array and chimneys Identical installation conditions are considered for each array configuration when observing the shading effects by taking into account the sun path. The same settling and surrounding operating conditions on the roof-top area allow fair comparisons between payback times of the different PV array configurations. Shadowing model involves complex trigonometric equations which are based on the 3D imagination of the sun moving and geometric structures [19]. The geometric information of the PV modules and obstacles is necessary for virtual reality simulations. Besides that solar angles which represent the movement of the sun are needed to study in the virtual reality world [19]. The illustration of shadowing process is depicted in Fig. 3. Fig. 3. BIPV system shading method The shadowing calculations are performed based on the previous study [15] that presents the structure of trigonometric equations and procedures of the shadowing model for a PV array. The 7 methodology is summarized in Fig. 4. The process is based on the time of the day and the geographic location of the examined area (latitude angle). Shadow lengths are determined by using obstacle lengths and the solar angles which are determined by the time and latitude angle. After calculation of the shadow lengths, shaded PV modules are determined by the comparison of the PV module location and shadow location on the surface of PV modules. If shadow points are observed between the edges of the PV modules, then “PV module is shadowed” decision is assigned. The same process is repeated for all PV modules in the field and then the electrical characteristics of PV array configurations are observed [15]. The physical variables for calculation of the shadows are given in Table 2 in this study. Table 2 Physical variables of the system for partial shading analysis Parameters Values Roof Tilt Angle 30° Roof Azimuth Angle 0° (South faced) Chimney Lengths 750x750x2000 mm Module Lengths 1510x674x50 mm Distance Between Modules 100 mm Distance Between Chimney and a Module 100 mm Latitude Angle 38.42° E 8 Fig 4. Flowchart of shadow detection [15] 4. SP and TCT Configurations In this section, the basic electrical behaviors of SP and TCT configurations are presented. The SP and TCT configuration types are represented in Fig. 5 for 2x2 PV array. Fig. 5. SP and TCT configurations for 2x2 PV array When both PV array configurations are operating under the same irradiance conditions, the different current and output power values are obtained at the global MPP. They are given in Table 3. Table 3 The current and power at the global MPP for 2x2 SP and TCT configurations 9 Fig. 9. 6x4 PV array connection with shading effect Fig. 10. 8x3 PV array connection with shading effect In Tables 7 and 8, the output currents of the PV modules and tie line currents are given for TCT configurations. In 8x3 TCT configuration, the currents at local and global MPPs are the same. Table 7 Module current values of 6x4 and 8x3 TCT configurations at local (LP) and global (GP) MPPs C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 6x4 LP GP 7.95 11.15 7.86 8.08 4.30 7.48 4.30 7.48 4.30 7.48 4.30 7.48 0.65 3.81 0.74 6.88 4.30 7.48 4.30 7.48 4.30 7.48 4.30 7.48 6x4 8x3 LP/GP 5.40 5.40 5.40 5.40 7.83 7.74 0.56 0.74 5.40 5.40 5.40 5.40 C13 C14 C15 C16 C17 C18 C19 C20 C21 C22 C23 C24 6x4 LP GP 0.65 3.81 0.74 6.88 4.30 7.48 4.30 7.48 4.30 7.48 4.30 7.48 7.95 11.15 7.86 8.08 4.30 7.48 4.30 7.48 4.30 7.48 4.30 7.48 6x4 8x3 LP/GP 0.56 0.74 7.83 7.74 5.40 5.40 5.40 5.40 7.83 7.74 7.82 7.74 16 Table 8 Link current values of 6x4 and 8x3 TCT configurations L1 L2 L3 L4 L5 L6 L7 L8 L9 L10 L11 L12 L13 L14 6x4 LP GP -0.09 -3.07 -3.56 -0.60 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.09 3.07 3.56 0.60 0 0 0 0 8x3LP/GP 0 0 0 2.42 -0.08 -7.18 0.17 0 0 0 -2.42 0.08 -0.08 0.08 When local MPPs of SP connections are considered, it can be clearly seen that 6x4 connection type shows better performance than 8x3 connection. While the half of the string of 6x4 connection is shaded, the string of in 8x3 connection 2/3 of the string is shaded. It means that more PV modules are affected from shadowing in 8x3 connection. This impact can be seen on the local MPPs clearly. In all cases, TCT configurations show better performance when considering powers at local MPPs. The reason of this result is due to the tie lines that support alternative current paths. These alternative paths help to avoid limiting the currents in same string due to the partially shaded PV modules. In TCT connection, tie lines have a significant effect on the current flows. It causes to change the individual MPP of each PV module and this result in the change of the output power of PV arrays. 7. Discussion Small scale PV systems have rapidly increased in urban areas over the past decade. In urban areas, a large amount of empty rooftop spaces are ideal locations for PV modules. However, shadows of neighboring objects significantly cause to decrease performance of the PV system. The impact of shadow changes due to the movement of the sun. In this study, chimneys which are located on the residential roof-top area are considered to create the effect of shading over the PV array. The locations of PV modules are kept stationary, which is the main point of this paper, while comparing the performances of the different electrical configurations with the same surrounding obstacles that causes partial shading conditions. The purpose of this study is to 17 investigate the potential for improving the long-term efficiency of PV arrays by finding out the best electrical configuration under the partially shaded conditions by analyzing annual energy generation of the same BIPV system, in terms of nominal power, without changing physical locations of the PV modules in the PV arrays. For this purpose, the spatial structure of the PV system including the PV modules and the surrounding obstacles is taken into account on the basis of virtual reality environment. On the other hand, utility poles, trees, other buildings, and other parts of the same building may also cause shadows on the PV modules in urban areas. In addition to that, PV systems are not only installed on the rooftop of the buildings, but also all surfaces of the high rise buildings [21]. So, the PV modules can be shaded by different type of objects. Depending on the building rotation and structure, tilt and azimuth angles of PV modules are important parameters for PV systems. As a result, geometric details of the rooftop and surrounding obstacles affect calculation of the shadows on the PV arrays [22]. Because of different installation parameters, annually energy output of the PV arrays will be different [23]. In the present study, results show that it is possible to improve the long-term performance of the partially shaded PV array by considering different electrical connections of PV array. It is worth noting that advanced and detailed simulation analysis will be more important to estimate the harvested energy from PV arrays in urban areas. This kind of analysis must be applied before mounting the PV modules on the buildings considering surrounding shadow factors. 8. Conclusions In this paper, different electrical connected PV arrays are analyzed under realistic partial shading conditions without changing physical locations of PV modules in the PV arrays. The powervoltage characteristics of PV array strongly depend on which PV modules are shaded in the electrical connection of PV array. The performance analyses are performed by two different 18 payback times to compare economic advantages of the PV electrical configurations. The main aim of this study is to show that if the field area of PV modules is restricted and it is not possible to change the location of PV modules due to the partial shading effect, it is possible to improve the system efficiency by only changing the electrical configuration of PV array. It is possible to determine which connection type is the best for the interested PV installation field by taking into account of the surrounding obstacles such as chimney on the roof before installation of PV systems. In this study, 24 PV modules are used on the rooftop area and the connection of the PV modules is changed such as 2x12, 3x8, 4x6, 6x4, 8x3, and 12x2 for configuration types of TCT and SP. The spatial shadow behaviors are incorporated to the location of PV modules on the rooftop area with the chimneys. The results show that the different configurations and connection types of PV arrays have a significant impact on the partially shaded PV arrays and the payback time. 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